Quantification of uncertainty in spatial data for ecological applications

Principal Investigators:

Carolyn T. Hunsaker

Land cover maps are a primary data source for persons designing reserves,
working on management plans for sensitive species, and performing ecological
risk assessments. Maps are generalizations of reality and contain spatial
uncertainty from the generalization which should be quantified for
ecological applications. We propose to develop a spatial statistical
approach that can deal comprehensively with the problem of error propagation
and provide a bridge between the distinct traditions of remote sensing and
Geographic Information... more

Land cover maps are a primary data source for persons designing reserves,
working on management plans for sensitive species, and performing ecological
risk assessments. Maps are generalizations of reality and contain spatial
uncertainty from the generalization which should be quantified for
ecological applications. We propose to develop a spatial statistical
approach that can deal comprehensively with the problem of error propagation
and provide a bridge between the distinct traditions of remote sensing and
Geographic Information Systems. One or more case studies illustrating the
approach would be undertaken by an interdisciplinary team, and a specialists
meeting would provide input during the first year of work.